Octo-planner: On-device Language Model for Planner-Action Agents

arXiv:2406.18082v1 Announce Type: new
Abstract: AI agents have become increasingly significant in various domains, enabling autonomous decision-making and problem-solving. To function effectively, these agents require a planning process that determines the best course of action and then executes the planned actions. In this paper, we present an efficient on-device Planner-Action framework that separates planning and action execution into two distinct components: a planner agent based on Phi-3 Mini, a 3.8 billion parameter LLM optimized for edge devices, and an action …

action agents arxiv cs.cl cs.hc device language language model type